Sharif Digital Repository

Properly adjusting the trim angle during the craft speed up, plays an important role in easily passing through the resistance hump and to reach final speed in minimum possible time. Present study tries to reply to this question that how the angles applied to a trimmable drive system and trim tab of the planing craft should be changed during speed up from rest, to craft reach a final speed in minimum time. This is a time-optimal control problem with the drive and trim tab angles as its control variables. To solve this problem a 3-DOF dynamic model is developed here rely on empirical data and relations. For the propulsion system operation of propeller, drive and engine altogether are taken... 

The vanillin assay is a spectrophotometric method for anthocyanin determination that is simple, quick and inexpensive. The method is preferred because of its high sensitivity, specificity and simplicity; however, the results of this test are influenced by several factors. Hence, a D-optimal experimental design approach was investigated to simultaneously, without loss of information, optimize five factors that influence the vanillin assay: acid normality, vanillin concentration, temperature, time and acid type. Further optimization with a D-optimal design and response surface analysis (RSM) showed that a second-order polynomial model fit the experimental data appropriately. The optimum... 

This study proposes an imperialist competition algorithm (ICA) to maximise the benefits of distribution network operators (DNOs) because of the existence of distributed generation (DG) units. The sum of active loss reduction and network investment deferral incentives has been considered as the objective function to be maximised in this study. The optimal location and size of DG units in the network are found considering various techno-economical issues. The application of the proposed methodology in the UK under current Ofgem financial incentives for DNOs is investigated. The ability of the proposed approach in finding the optimal solution is validated by comparing the obtained results with... 

In this paper, we consider the problem of Minimum-Cost Multicast (MCM) sub-graph optimization with network coding subject to uncertainty in link costs. A number of uncertainty sets such as ellipsoids and bounded polyhedral are taken into account. A robust optimization model is developed to obtain the optimal sub-graph by replacing an uncertain model of MCM by its Robust Counterpart (RC). Then, the analytic and computational optimization tools to obtain robust solutions of an uncertain MCM problem via solving the corresponding explicitly-stated convex RC program is developed and validated through simulations  

Within-die process variation is increasing in nanometer-scale process technologies. We observe that the same SRAM cell leaks differently under within-die process variations when storing 0 compared to 1; this difference can be up to 3 orders of magnitude at 60mV variation of threshold voltage (V th). Thus, leakage can be reduced if most often the values that dissipate less leakage are stored in the cache SRAM cells. We take advantage of this fact to reduce instruction-cache leakage by presenting three binary-optimization and software-level techniques: we (i) reorder instructions within basic-blocks so that their bits better match the less-leaky state of their corresponding cache cells, (ii)... 

A practical optimization method is applied to design nonlinear truss-like structures subjected to seismic excitation. To achieve minimum weight design, inefficient material is gradually shifted from strong parts to weak parts of a structure until a state of uniform deformation prevails. By considering different truss structures, effects of seismic excitation, target ductility and buckling of the compression members on optimum topology are investigated. It is shown that the proposed method could lead to 60% less structural weight compared to optimization methods based on elastic behavior and equivalent static loads, and is efficient at controlling performance parameters under a design... 

Given measurement difficulties, earlier modeling studies have often used some constant ratios to predict lumbar segmental kinematics from measurements of total lumbar kinematics. Recent imaging studies suggested distribution of lumbar kinematics across its vertebrae changes with trunk rotation, lumbar posture, and presence of load. An optimization-based method is presented and validated in this study to predict segmental kinematics from measured total lumbar kinematics. Specifically, a kinematics-driven biomechanical model of the spine is used in a heuristic optimization procedure to obtain a set of segmental kinematics that, when prescribed to the model, were associated with the minimum... 

Spectrum mobility in cognitive radio networks not only enables the secondary users to guarantee the desired QoS of the primary users but also grants an efficient exploitation of the available spectrum holes in the network. In this paper, we propose a probabilistic approach in determining the initial and target channels for the handoff procedure in a single secondary user network. To characterize the network, a queuing theoretical framework is introduced, and 'stay' and 'change' handoff policies are both addressed. The performance of the secondary user in terms of average sojourn and extended service times for secondary connections is analyzed, and convex optimization problems with the... 

A central problem in motor control is to understand how the many biomechanical degrees of freedom are coordinated to achieve a goal. A common assumption is that Central Nervous System (CNS) would minimize a performance index to achieve this goal which is called objective function. In this paper, two popular objective functions are utilized to design the optimal trajectory of trunk movements. A 3D computational method incorporated with 18 anatomically oriented muscles is used to simulate human trunk system. Inverse dynamics allows us to compute torque which is generated around Lumbosacral joint. This torque is divided among muscles by static stability-based optimization. Trunk movement from... 

We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach identifies vectors that are orthogonal to the subspaces in which the training data concentrate. We study conditions on the coefficients of training data that guarantee that ideal normal vectors deduced from the dictionary are local optima of the criterion. We illustrate the behavior of the criterion on a 2D example, showing that the local minima correspond to ideal normal vectors when the number of training data is sufficient. We conclude by describing an algorithm that can be used to optimize the criterion in higher... 

The problem of clustering with side information has received much recent attention and metric learning has been considered as a powerful approach to this problem. Until now, various metric learning methods have been proposed for semi-supervised clustering. Although some of the existing methods can use both positive (must-link) and negative (cannot-link) constraints, they are usually limited to learning a linear transformation (i.e., finding a global Mahalanobis metric). In this paper, we propose a framework for learning linear and non-linear transformations efficiently. We use both positive and negative constraints and also the intrinsic topological structure of data. We formulate our metric... 

Deregulation in power systems has created new uncertainties and increased the previous ones. The presence of these uncertainties, high investment costs, and long period investment return cause the transmission network to remain monopoly and the private investors not being interested in investing in this section. This paper presents a new approach for transmission expansion planning (TEP) in order to maximize private investment absorption. The robust optimization method is used to model the inherent uncertainties associated with the estimated investment cost of candidate lines and the forecasted system load. The genetic algorithm (GA) is, also, utilized as the methodology to solve the... 

Human bodies use the electrical currents to make the muscles move. Disconnection of the electrical signals between the brain and the muscles as a result of spinal cord injuries, causes paralysis below the level of injury. Functional electrical stimulation (FES) is used to stimulate the peripheral nerves of the disabled limbs. The level of these electrical signals should be selected so that the desired tasks are done successfully. Applying the appropriate controller which can result a human like behaviour and the accomplishment of the desired tasks has become a significant research area. In this paper, the multi-input multi-output (MIMO) musculoskeletal model of human arm with six muscles is... 

A new method for structural optimization is presented for successive approximation of the objective function and constraints in conjunction with Lagrange multipliers approach. The focus is on presenting the methodology with simple examples. The basis of the iterative algorithm is that after each iteration, it brings the approximate location of the estimated minimum closer to the exact location, gradually. In other words, instead of the linear or parabolic term used in Taylor expansion, which works based on a short step length, an arch is used that has a constant curvature but a longer step length. Using this approximation, the equations of optimization involve the Lagrange multipliers as the... 

This paper present a simple watermarking approach based on the rotation of low frequency components of image blocks. The rotation process is performed with less distortion by projection of the samples on specific lines according to message bit. To have optimal detection Maximum Likelihood criteria has been used. Thus, by computing the distribution of rotated noisy samples the optimum decoder is presented and its performance is analytically investigated. The privilege of this proposed algorithm is its inherent robustness against gain attack as well as its simplicity. Experimental results confirm the validity of the analytical derivations and also high robustness against common attacks. ©... 

We study the tradeoff between the sum rate and the error probability in downlink of wireless networks. Using the recent results on the achievable rates of finite-length codewords, the problem is cast as a joint optimization of the network sum rate and the per-user error probability. Moreover, we develop an efficient algorithm based on the divide-and-conquer technique to simultaneously maximize the network sum rate and minimize the maximum users’ error probability and to evaluate the effect of the codeword length on the system performance. The results show that, in delay-constrained scenarios, optimizing the per-user error probability plays a key role in achieving high throughput. IEEE  

Remote control switches (RCSs) are often assumed to be fully reliable in reliability and cost/worth analyses. This assumption, however, overestimates their merits, thereby misguiding network owners about their optimal implementation. This letter extends the current reliability evaluation procedure to incorporate probability of RCS malfunctions. Then, the extended procedure is applied to a network equipped with a few RCSs. The numerical studies reveal that RCS malfunctions degrade their worth, which may even affect their optimal number and locations. © 1969-2012 IEEE  

A mechanical system inherently affected by the conditions, factors, and parameters of uncertainties. Without including the uncertainty effects in the design procedure, the designs may not be robust and reliable. Robust design optimization (RDO) method is a procedure to find the insensitive design with respect to the variations. On the other hand, reliability is measured by the probability of satisfying a specific design criterion. Therefore, a reliable design is a design that satisfies the specified criteria even with some uncertainties in variables and parameters. Reliability-based design optimization (RBDO) is an optimization procedure that incorporates reliability requirements to find the... 

In this paper, we investigate the implementation of wavelet modulation (WM) in a digital communication system and propose novel methods to improve its performance. We will put particular focus on the structure of an optimal detector in AWGN channels and address two main methods for inserting the samples of the message signal in different frequency layers. Finally, computer based algorithms are described in order to implement and optimize receivers and transmitters  

Submodularity is a discrete domain functional property that can be interpreted as mimicking the role of well-known convexity/concavity properties in the continuous domain. Submodular functions exhibit strong structure that lead to efficient optimization algorithms with provable near-optimality guarantees. These characteristics, namely, efficiency and provable performance bounds, are of particular interest for signal processing (SP) and machine learning (ML) practitioners, as a variety of discrete optimization problems are encountered in a wide range of applications. Conventionally, two general approaches exist to solve discrete problems: 1) relaxation into the continuous domain to obtain an...